CN105390029A - Ship collision avoidance assisted decision-making method and system based on track fusion and track prediction - Google Patents
Ship collision avoidance assisted decision-making method and system based on track fusion and track prediction Download PDFInfo
- Publication number
- CN105390029A CN105390029A CN201510755138.7A CN201510755138A CN105390029A CN 105390029 A CN105390029 A CN 105390029A CN 201510755138 A CN201510755138 A CN 201510755138A CN 105390029 A CN105390029 A CN 105390029A
- Authority
- CN
- China
- Prior art keywords
- ship
- information
- track
- module
- collision
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 65
- 230000004927 fusion Effects 0.000 title claims abstract description 60
- 238000012544 monitoring process Methods 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 15
- 238000011156 evaluation Methods 0.000 claims abstract description 6
- 230000002265 prevention Effects 0.000 claims description 36
- 238000012545 processing Methods 0.000 claims description 17
- 239000002131 composite material Substances 0.000 claims description 12
- 230000003993 interaction Effects 0.000 claims description 10
- 238000012502 risk assessment Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004891 communication Methods 0.000 claims description 7
- 230000006870 function Effects 0.000 claims description 7
- 230000005540 biological transmission Effects 0.000 claims description 5
- 239000003086 colorant Substances 0.000 claims description 5
- 238000006243 chemical reaction Methods 0.000 claims description 4
- 238000007499 fusion processing Methods 0.000 claims description 4
- 230000010365 information processing Effects 0.000 claims description 4
- 238000009877 rendering Methods 0.000 claims description 4
- 230000002123 temporal effect Effects 0.000 claims description 4
- 238000011161 development Methods 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 4
- 238000001914 filtration Methods 0.000 description 4
- LFULEKSKNZEWOE-UHFFFAOYSA-N propanil Chemical compound CCC(=O)NC1=CC=C(Cl)C(Cl)=C1 LFULEKSKNZEWOE-UHFFFAOYSA-N 0.000 description 4
- 230000003068 static effect Effects 0.000 description 3
- 238000013459 approach Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- QZXCCPZJCKEPSA-UHFFFAOYSA-N chlorfenac Chemical compound OC(=O)CC1=C(Cl)C=CC(Cl)=C1Cl QZXCCPZJCKEPSA-UHFFFAOYSA-N 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000009966 trimming Methods 0.000 description 1
Landscapes
- Traffic Control Systems (AREA)
Abstract
The invention discloses a ship collision avoidance assisted decision-making method and system based on track fusion and track prediction. The method comprises the following steps: S1, ship information transmitted by an automatic identification system of a ship and a radar is obtained and pretreatment is carried out on the ship information to obtain position, speed, and orientation information of the ship; S2, track association and track fusion are carried out on the position, speed, and orientation information of ship; and S3, according to the result of the track fusion, track prediction is carried out on a target ship, and ship collision risk evaluation, avoidance decision making, and target ship posture monitoring are carried out. According to the invention, reliability and stability of the ship navigation data source are improved; safety information during the ship sailing process can be monitored intelligent in real time; and thus the ship collision can be avoided. Intelligence and miniaturization of the ship-borne equipment can be realized well; and the method and system have great practical application values.
Description
Technical field
The present invention relates to ship collision prevention technical field, particularly relate to a kind of ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction and system.
Background technology
Ship collision is major accident kind in navigation safety always, and the collision accident of more than 80% is directly or indirectly caused by human factor.At present, most Collision Avoidance of Ships is by operating personnel's empirically subjective decision, and accuracy and the standardization of its operation can not ensure.Visible, in order to reduce the generation of Collision Accidents of Ships, emphasis to reduce the nonstandard or invalid measures to keep clear of operating personnel.Therefore, in the urgent need to a kind of navigation environment that marine navigator can be allowed to understand boats and ships in real time, pellucidly, and the ship collision prevention system of anti-collision warning and avoidingcollis ionscheme can be provided, for reducing the collision accident that human factor causes for it.But also have a lot of not enough in existing ship collision prevention systematic research achievement, show the following aspects:
1, conventional boat-carrying navigational aid has marine radar and ship automatic identification system (AIS), can obtain target information, but both respectively has relative merits, so use triangular web to be difficult to the accuracy of guarantee information and comprehensive.
2, in actual motion, AIS equipment may occur that information sends unsuccessfully, and radar may have blind area, and this all can cause this ship cannot receive up-to-date information in time.On the other hand, realize ship collision prevention warning function, not only will make Risk-Degree of Collision analysis to current, also want to make analysis to position relationship new between subsequent time boats and ships, this could make measures to keep clear to dangerous situation in advance.
3, in ship collision prevention analysis and this technical field of aid decision making, also there is no quantitative model accurately at present, do not have to consider the position relationship detecting target and this ship, and analyze current risk of collision, the system of early warning scheme is provided.
4, embedding assembly and computer calculate develop rapidly at present, and ship collision prevention field does not also have can in conjunction with the system of the intellectuality of these technology, robotization.
Summary of the invention
The technical problem to be solved in the present invention is for boat-carrying navigational aid reliability single in prior art poor, and the defect of ship collision early warning can not be provided automatically, provide a kind of can robotization, the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of Intelligent Calculation ship navigation state and system.
The technical solution adopted for the present invention to solve the technical problems is:
The invention provides a kind of ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction, comprise the following steps:
S1, obtain the ship information of ship automatic identification system and radar transmissions, and pre-service is carried out to it obtain the position of boats and ships, speed and azimuth information;
S2, position to boats and ships, speed and azimuth information carry out track association and Track Fusion, and concrete steps are:
S21, position to boats and ships, speed and azimuth information carry out coordinate conversion and temporal registration, and longitude and latitude form information is converted to polar form information, use piecewise linear interpolation method by nonsynchronous information unification to synchronization;
S22, track association is carried out to the position after process, speed and azimuth information, with object ship ship automatic identification system flight path information for benchmark, first to get rid of compared with ship automatic identification system information time, range difference apart from larger radar track information; Pass through the correlation degree of Ship ' automatic recognition system flight path information and radar track information again, to the radar track information that more options correlation degree is larger, this ship automatic identification system flight path information and radar information are chosen to be the object of object ship Track Fusion;
S23, Track Fusion is carried out to the ship automatic identification system of the larger object ship of selected correlation degree and radar track information, adopt the Weighted estimation method of Corpus--based Method to complete the Track Fusion process of object ship, and store fusion results for Trajectory Prediction data are provided;
S3, according to the result of Track Fusion, Trajectory Prediction is carried out to object ship, and make ship collision Risk Assessments, dodge decision-making and the monitoring of object ship situation.
Carry out pretreated method to ship information in step S1 to be specially:
Resolve according to ship automatic identification system and radar message format respectively, and extract effective information and be stored in database.
In step S2, the ship automatic identification system flight path information of object ship and the computing method of radar track information association degree are specially:
By the membership function of normal distribution obtain distance, orientation, the speed of a ship or plane, these 4 factors of course Euclidean distance association with do not associate degree of membership value, then be weighted with each factor weight size and on average can obtain composite factor and associate and do not associate degree of membership;
Finally carry out double threshold carefully to associate, namely judge composite factor association degree of membership maximal value and meet the whether satisfied threshold value set of thin degree of incidence, if all meet, association is stopped to judge, store and bind ship automatic identification system and the radar label of the object ship judging thin association, as the object of the larger object ship Track Fusion of correlation degree.
In step S3, the method for ship collision Risk Assessments is specially:
Consider least meeting distance, minimum can meet the time, two ships distances, object ship and this angle, bearing, this ship and object ship speed than these 5 as factor of evaluation, obtain composite factor Risk-Degree of Collision with its respective weights value weighting after obtaining respective degree of membership.
The method dodging decision-making in step S3 is specially:
First Anti-collision Actions opportunity is determined, the method of risk of collision topology degree is adopted to calculate Risk-Degree of Collision, and itself and the risk factor threshold value set are compared, if be greater than this threshold value, meet situation according to this ship with the meeting of object ship to judge to dodge mode, determine that this ship is stand-on vessel or dodges ship, and still dodge to the right left; Finally determine turning avoidance amplitude.
In step S3, the method for object ship situation monitoring is specially:
With this ship for rectangular coordinate system center origin, real-time rendering also shows monitoring objective position around this ship within the scope of 8 nautical miles, course information and flight path, and intuitively can reflect different risk of collision level state by different colours drafting target, click corresponding target and can show corresponding information and dodge suggestion.
The invention provides a kind of ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction, comprise serial ports receiver module and database, and all with the message processing module of described DataBase combining, algoritic module and human-computer interaction module, described serial ports receiver module is connected with described message processing module;
Described message processing module, comprise ship automatic identification system message processing module, radar information processing module and other message processing modules, for receiving the shipping information sent from serial ports receiver module, and pre-service is carried out to it obtain the position of boats and ships, speed, azimuth information, finally result is saved in database;
Described algoritic module, comprise data anastomosing algorithm module, Trajectory Prediction algoritic module, dodge decision making algorithm module, risk of collision algoritic module and other algoritic modules, for reading the position of boats and ships, speed, azimuth information from data memory module, and Track Fusion and Trajectory Prediction are carried out to it, carry out anti-collision warning according to result of calculation and dodge decision-making;
Described human-computer interaction module, comprises target situation monitoring module, information inquiry module, anti-collision warning module, system configuration module and other functional modules, for the sail information of real-time display boats and ships, and various early warning information.
This system adopts linux embedded system to be development platform, and database adopts SQLite3, and IDK adopts QT, hardware ARM plate to adopt S3C6410 chip as processor.
This system also comprises GPRS communication module, and is communicated with Surveillance center by described GPRS communication module.
Described human-computer interaction module adopts touch-screen to carry out man-machine interaction.
The beneficial effect that the present invention produces is: the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the present invention, by shipborne radar and AIS system are combined, still can analyze Collision Risk Index when ensure that triangular web lost efficacy, improve the reliability and stability of Data Source; On the other hand, by Track Fusion and Trajectory Prediction algorithm, risk of collision during ship's navigation is analyzed, and make dodge decision-making and target situation monitoring, can be real-time, intelligence monitoring ship's navigation time security information, avoid boats and ships to collide; And in conjunction with embedded technology and computer technology, improve the reliability of system, extensibility, and contribute to intellectuality and the miniaturization of ship-borne equipment, there is good actual application value.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the invention will be further described, in accompanying drawing:
Fig. 1 is the process flow diagram of the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the embodiment of the present invention;
Fig. 2 is the workflow diagram of the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the embodiment of the present invention;
Fig. 3 is the structured flowchart of the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction of the embodiment of the present invention;
Fig. 4 is the hardware configuration schematic diagram of the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction of the embodiment of the present invention;
Fig. 5 be the embodiment of the present invention based on prediction algorithm process flow diagram in the ship collision prevention aid decision-making method of Track Fusion and Trajectory Prediction;
Fig. 6 is the ship motion polar plot of the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the embodiment of the present invention.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
As shown in Figure 1, the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the embodiment of the present invention, comprises the following steps:
S1, obtain the ship information of ship automatic identification system and radar transmissions, and pre-service is carried out to it obtain the position of boats and ships, speed and azimuth information; Resolve according to ship automatic identification system and radar message format respectively, and extract effective information and be stored in database.
S2, position to boats and ships, speed and azimuth information carry out track association and Track Fusion, and concrete steps are:
S21, position to boats and ships, speed and azimuth information carry out coordinate conversion and temporal registration, and longitude and latitude form information is converted to polar form information, use piecewise linear interpolation method by nonsynchronous information unification to synchronization;
S22, track association is carried out to the position after process, speed and azimuth information, with object ship ship automatic identification system flight path information for benchmark, first to get rid of compared with ship automatic identification system information time, range difference apart from larger radar track information; Pass through the correlation degree of Ship ' automatic recognition system flight path information and radar track information again, to the radar track information that more options correlation degree is larger, this ship automatic identification system flight path information and radar information are chosen to be the object of object ship Track Fusion;
The computing method of correlation degree are specially:
By the membership function of normal distribution obtain distance, orientation, the speed of a ship or plane, these 4 factors of course Euclidean distance association with do not associate degree of membership value, then be weighted with each factor weight size and on average can obtain composite factor and associate and do not associate degree of membership;
Finally carry out double threshold carefully to associate, namely judge composite factor association degree of membership maximal value and meet the whether satisfied threshold value set of thin degree of incidence, if all meet, association is stopped to judge, store and bind ship automatic identification system and the radar label of the object ship judging thin association, as the object of the larger object ship Track Fusion of correlation degree.
S23, Track Fusion is carried out to the ship automatic identification system of the larger object ship of selected correlation degree and radar track information, adopt the Weighted estimation method of Corpus--based Method to complete the Track Fusion process of object ship, and store fusion results for Trajectory Prediction data are provided;
S3, according to the result of Track Fusion, Trajectory Prediction is carried out to object ship, and make ship collision Risk Assessments, dodge decision-making and the monitoring of object ship situation.
The method of ship collision Risk Assessments is specially:
Consider least meeting distance, minimum can meet the time, two ships distances, object ship and this angle, bearing, this ship and object ship speed than these 5 as factor of evaluation, obtain composite factor Risk-Degree of Collision with its respective weights value weighting after obtaining respective degree of membership.
The method dodging decision-making is specially:
First Anti-collision Actions opportunity is determined, the method of risk of collision topology degree is adopted to calculate Risk-Degree of Collision, and itself and the risk factor threshold value set are compared, if be greater than this threshold value, meet situation according to this ship with the meeting of object ship to judge to dodge mode, determine that this ship is stand-on vessel or dodges ship, and still dodge to the right left; Finally determine turning avoidance amplitude.
The method of object ship situation monitoring is specially:
With this ship for rectangular coordinate system center origin, real-time rendering also shows monitoring objective position around this ship within the scope of 8 nautical miles, course information and flight path, and intuitively can reflect different risk of collision level state by different colours drafting target, click corresponding target and can show corresponding information and dodge suggestion.
As shown in Figure 2, in an alternative embodiment of the invention, for once complete auxiliary collision prevention process, according to data processing and pass order, its workflow is specially:
(1) received the message of AIS module, radar module transmission by serial ports, obtain target information;
(2) according to the message information format analysis of AIS and radar, extract information needed and be also stored in database;
(3) from static, dynamically several data, take out and merge desired location, speed and azimuth information, carry out data fusion, flight path is merged in display, is in order to ensure the correctness in quantitative analysis source and comprehensive like this;
(4) according to fusion flight path, predict next step target location, speed and azimuth information, the Data Source of collision prevention analysis and anti-collision warning is provided, and ensure that the promptness that subsequent analysis judges;
(5) according to information of forecasting, judgement can meet situation, and is presented at all targets in the certain limit centered by this ship, allows operating personnel intuitively grasp navigation environment integral status around;
(6) whether assessment has risk of collision, and this is the core of ship collision prevention system, and evaluation method should have validity and rapidity;
(7) if judge dangerous, then anti-collision warning is provided;
(8) according to situation can be met, the scheme of dodging is provided.
As shown in Figure 3, the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction of the embodiment of the present invention is for realizing the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction of the embodiment of the present invention, comprise serial ports receiver module and database, and all with the message processing module of described DataBase combining, algoritic module and human-computer interaction module, described serial ports receiver module is connected with described message processing module;
Described message processing module, comprise ship automatic identification system message processing module, radar information processing module and other message processing modules, for receiving the shipping information sent from serial ports receiver module, and pre-service is carried out to it obtain the position of boats and ships, speed and azimuth information, finally result is saved in database;
Described algoritic module, comprise data anastomosing algorithm module, Trajectory Prediction algoritic module, dodge decision making algorithm module, risk of collision algoritic module and other algoritic modules, for reading the position of boats and ships, speed and azimuth information from data memory module, and Track Fusion and Trajectory Prediction are carried out to it, carry out anti-collision warning according to result of calculation and dodge decision-making;
Described human-computer interaction module, comprises target situation monitoring module, information inquiry module, anti-collision warning module, system configuration module and other functional modules, for the sail information of real-time display boats and ships, and various early warning information.
In an alternative embodiment of the invention, the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction provided by the invention, specifically comprises:
1. serial ports receiver module
The device that the present invention's correspondence realizes is connected with radar module with AIS by serial ports, and its hardware configuration schematic diagram as shown in Figure 4, obtains the message information of AIS and radar transmissions by serial ports receiver module program loop.
2. message processing module
Comprise AIS and radar information processing module, namely to the information that serial ports receiver module obtains, resolve according to AIS and radar message format respectively, and extract effective information and be stored in database.
4. data anastomosing algorithm module
Data fusion is carried out to the position of AIS and radar target, speed and azimuth information, specifically comprises:
(1) coordinate conversion: because radar target position is the distance and bearing form of polar coordinate system, AIS is longitude and latitude form information.In order to unified coordinate system is convenient to follow-up data process, be used as circle to process positional information approximate for earth ellipsoid face, AIS latitude and longitude information is converted to polar coordinates.
(2) temporal registration: unified to synchronization to nonsynchronous metric data of same target, these are normally different due to multiple sensor sample cycle, and the moment that system acceptance arrives is also different.Adopt the subsection linearity inser value method of comparatively simple possible, its principle is coupled together by interpolation point broken line, thus more approach original function.
3) track association: first carry out time gap and slightly associate, can get rid of time, range difference apart from larger target, as several hours or tens nautical miles, drastically reduce the area like this and need follow-up judgement affiliated partner, improve counting yield; Then fuzzy comprehensive evoluation plot-track Association Algorithm is carried out, by the membership function of normal distribution obtain distance, orientation, the speed of a ship or plane, these 4 factors of course Euclidean distance association with do not associate degree of membership value, then be weighted with each factor weight size and on average can obtain composite factor and associate and do not associate degree of membership; Finally carry out double threshold carefully to associate, namely judge composite factor association degree of membership maximal value and meet the whether satisfied threshold value set of thin degree of incidence, if all meet, stop association judging, store and bind the AIS and radar target label that judge thin association, determining the boats and ships object of Track Fusion.
(4) Track Fusion: adopt the Weighted estimation method of Corpus--based Method to complete targetpath fusion process, when total mean square error is minimum, determine optimal weighted factor, thus ensure that the estimated value after merging reaches the most accurate, the method is simple and easy to realize.Last fusion results stored in database, for Trajectory Prediction provides fusion track data.
5. Trajectory Prediction algoritic module
Adopt the Sage-Husa Adaptive Kalman Filtering Algorithm improved, the basis of Kalman filter adds the statistical property of measurement noise is estimated, and adopt the filtering convergence criterion based on covariances-matching techniques to prevent filtering divergence, according to information use order, the time can be divided into upgrade (estimating process) and measure and upgrade (trimming process), the interleaved computation of these two processes, then complete recursive filtering process.Specific algorithm process as shown in Figure 5, predicts the outcome as calculating state vector in Fig. 5
, by it stored in database.
6. risk of collision algoritic module
Comprise motion vector analysis, can meet that situation divides, ship collision Risk Assessments algorithm, detailed process: goal in research is used as particle, that in rectangular coordinate system, analyzes this ship and target specifically can meet situation, as shown in Figure 6.
Ship collision Risk Assessments model, chooses least meeting distance DCPA, the minimum velocity ratio K (K=V that can meet time TCPA, two ship distance D, object ship and this angle, bearing Δ B, this ship and object ship
t/ V
o) these 5 as factor of evaluation.The parameter that subsequent analysis needs can be obtained, wherein:
DCPA=D×sin(C
OT-B
T)
Then according to B
oTwith Δ C, can meet that situation is quantitatively divided into end-on, starboard intersect meet, larboard intersects and meets, overtakes, overtaken this 5 kinds of situation; Eventually through the value specifically being quantized Risk-Degree of Collision of ship collision Risk Assessments model, and by it stored in database.
And pass through
obtain final composite factor Risk-Degree of Collision.A
dCPA, a
tCPA, a
d, a
Δ B, a
kfor the respective weights of object ship parameter, all belong to [0,1], whole sum is 1, and corresponding membership function is:
Wherein, d
1represent the minor increment that two ships cross safely, d
2represent that safety can meet scope, r
1represent ship collision distance; r
2represent that boats and ships note distance, t
1represent the ship collision time, t
2represent that the time noted by boats and ships, C is for touching angle, and W is constant, and native system gets 2.0.
7. dodge decision making algorithm module
First determining Anti-collision Actions opportunity, is the method adopting risk of collision topology degree, the risk factor threshold value namely set.If Risk-Degree of Collision CRI is greater than this value, start to dodge; Then judge to dodge mode according to current situation of meeting, determine that this ship is stand-on vessel or dodges ship, and still dodge to the right left; Finally determine turning avoidance amplitude, adopt increasing step length to ask for steering angle θ
c, be progressively increased to satisfied | DCPA ' |>=SDA ', now θ
cbeing steering angle size, considering that ship turning has certain delay in actual conditions, and take Anti-collision Actions should " early ", for making result safer, reasonable, can the distance D in DCPA calculating formula suitably be reduced.
8. target situation monitoring modular
With this ship for rectangular coordinate system center origin, real-time rendering also shows monitoring objective position around this ship within the scope of 8 nautical miles, course information and flight path, and intuitively can reflect different risk of collision level state by different colours drafting target, native system represents that Risk-Degree of Collision higher (CRI >=0.5) suggestion is dodged at once by redness, yellow indicates that potential risk of collision (0≤CRI≤0.5) should pay close attention to target, green represent be safe from danger (CRI=0, two ships do not meet or through closest point of approach).
9. information inquiry module
Comprising the inquiry to this ship and target Ship dynamic situation, static information, and inquire about other historical datas at any time, after especially having an accident, can understand culprit like this, such as, is that after the not in place or monitoring, alarming of monitoring, human users is not in place.To finding out who is responsible for an accident, also whether correctly effectively can produce evidence to each operation of analysis like this.
10. anti-collision warning module
Risk of collision degree is divided into multiple warning level, the Risk-Degree of Collision obtained according to intellectual analysis and the threshold range made, can meet the different hazard types of boats and ships, carry out early warning to driver with different colours display, when it is very high that risk factor can be met, report to the police with sound.
11. system configuration module.
Ship information configures, the mainly static essential information such as name of vessel, ship launching time; Report to the police and to configure with threshold value of warning, be exactly according to the actual requirements (difference as goods) required warning value is set; Algorithm parameter configures, and can regulate according to real navigation environment.
Further, based on Track Fusion and Trajectory Prediction embedded ship collision prevention aid decision-making system with embedded system Linux, IDK QT, database SQLite 3 for Software Development Platform, using the S3C6410 chip ARM plate that is processor as hardware development platform, realize corresponding intrument.This device comprises embedded platform, AIS module, radar module, GPRS communication module and touch-screen, embedded platform is connected with radar information module, AIS information module, GPRS communication module, touch-screen, and this device is by GPRS communication module access Internet, thus communicates with Surveillance center.
Should be understood that, for those of ordinary skills, can be improved according to the above description or convert, and all these improve and convert the protection domain that all should belong to claims of the present invention.
Claims (10)
1., based on a ship collision prevention aid decision-making method for Track Fusion and Trajectory Prediction, it is characterized in that, comprise the following steps:
S1, obtain the ship information of ship automatic identification system and radar transmissions, and pre-service is carried out to it obtain the position of boats and ships, speed and azimuth information;
S2, position to boats and ships, speed and azimuth information carry out track association and Track Fusion, and concrete steps are:
S21, position to boats and ships, speed and azimuth information carry out coordinate conversion and temporal registration, and longitude and latitude form information is converted to polar form information, use piecewise linear interpolation method by nonsynchronous information unification to synchronization;
S22, track association is carried out to the position after process, speed and azimuth information, with object ship ship automatic identification system flight path information for benchmark, first to get rid of compared with ship automatic identification system information time, range difference apart from larger radar track information; Pass through the correlation degree of Ship ' automatic recognition system flight path information and radar track information again, to the radar track information that more options correlation degree is larger, this ship automatic identification system flight path information and radar information are chosen to be the object of object ship Track Fusion;
S23, Track Fusion is carried out to the ship automatic identification system of the larger object ship of selected correlation degree and radar track information, adopt the Weighted estimation method of Corpus--based Method to complete the Track Fusion process of object ship, and store fusion results for Trajectory Prediction data are provided;
S3, according to the result of Track Fusion, Trajectory Prediction is carried out to object ship, and make ship collision Risk Assessments, dodge decision-making and the monitoring of object ship situation.
2. the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction according to claim 1, is characterized in that, carry out pretreated method be specially in step S1 to ship information:
Resolve according to ship automatic identification system and radar message format respectively, and extract effective information and be stored in database.
3. the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction according to claim 1, it is characterized in that, in step S2, the ship automatic identification system flight path information of object ship and the computing method of radar track information association degree are specially:
By the membership function of normal distribution obtain distance, orientation, the speed of a ship or plane, these 4 factors of course Euclidean distance association with do not associate degree of membership value, then be weighted with each factor weight size and on average can obtain composite factor and associate and do not associate degree of membership;
Finally carry out double threshold carefully to associate, namely judge composite factor association degree of membership maximal value and meet the whether satisfied threshold value set of thin degree of incidence, if all meet, association is stopped to judge, store and bind ship automatic identification system and the radar label of the object ship judging thin association, as the object of the larger object ship Track Fusion of correlation degree.
4. the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction according to claim 1, it is characterized in that, in step S3, the method for ship collision Risk Assessments is specially:
Consider least meeting distance, minimum can meet the time, two ships distances, object ship and this angle, bearing, this ship and object ship speed than these 5 as factor of evaluation, obtain composite factor Risk-Degree of Collision with its respective weights value weighting after obtaining respective degree of membership.
5. the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction according to claim 1, it is characterized in that, the method dodging decision-making in step S3 is specially:
First Anti-collision Actions opportunity is determined, the method of risk of collision topology degree is adopted to calculate Risk-Degree of Collision, and itself and the risk factor threshold value set are compared, if be greater than this threshold value, meet situation according to this ship with the meeting of object ship to judge to dodge mode, determine that this ship is stand-on vessel or dodges ship, and still dodge to the right left; Finally determine turning avoidance amplitude.
6. the ship collision prevention aid decision-making method based on Track Fusion and Trajectory Prediction according to claim 1, is characterized in that, in step S3, the method for object ship situation monitoring is specially:
With this ship for rectangular coordinate system center origin, real-time rendering also shows monitoring objective position around this ship within the scope of 8 nautical miles, course information and flight path, and intuitively can reflect different risk of collision level state by different colours drafting target, click corresponding target and can show corresponding information and dodge suggestion.
7. the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction, it is characterized in that, comprise serial ports receiver module and database, and all with the message processing module of described DataBase combining, algoritic module and human-computer interaction module, described serial ports receiver module is connected with described message processing module;
Described message processing module, comprise ship automatic identification system message processing module, radar information processing module and other message processing modules, for receiving the shipping information sent from serial ports receiver module, and pre-service is carried out to it obtain the position of boats and ships, speed, azimuth information, finally result is saved in database;
Described algoritic module, comprise data anastomosing algorithm module, Trajectory Prediction algoritic module, dodge decision making algorithm module, risk of collision algoritic module and other algoritic modules, for reading the position of boats and ships, speed, azimuth information from data memory module, and Track Fusion and Trajectory Prediction are carried out to it, carry out anti-collision warning according to result of calculation and dodge decision-making;
Described human-computer interaction module, comprises target situation monitoring module, information inquiry module, anti-collision warning module, system configuration module and other functional modules, for the sail information of real-time display boats and ships, and various early warning information.
8. the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction according to claim 7, it is characterized in that, this system adopts linux embedded system to be development platform, database adopts SQLite3, IDK adopts QT, hardware ARM plate to adopt S3C6410 chip as processor.
9. the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction according to claim 7, it is characterized in that, this system also comprises GPRS communication module, and is communicated with Surveillance center by described GPRS communication module.
10. the ship collision prevention aid decision-making system based on Track Fusion and Trajectory Prediction according to claim 7, is characterized in that, described human-computer interaction module adopts touch-screen to carry out man-machine interaction.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510755138.7A CN105390029B (en) | 2015-11-06 | 2015-11-06 | Ship collision prevention aid decision-making method and system based on Track Fusion and Trajectory Prediction |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510755138.7A CN105390029B (en) | 2015-11-06 | 2015-11-06 | Ship collision prevention aid decision-making method and system based on Track Fusion and Trajectory Prediction |
Publications (2)
Publication Number | Publication Date |
---|---|
CN105390029A true CN105390029A (en) | 2016-03-09 |
CN105390029B CN105390029B (en) | 2019-04-26 |
Family
ID=55422265
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510755138.7A Expired - Fee Related CN105390029B (en) | 2015-11-06 | 2015-11-06 | Ship collision prevention aid decision-making method and system based on Track Fusion and Trajectory Prediction |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105390029B (en) |
Cited By (70)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105589464A (en) * | 2016-03-28 | 2016-05-18 | 哈尔滨工程大学 | UUV dynamic obstacle avoidance method based on speed obstruction method |
CN106017475A (en) * | 2016-07-04 | 2016-10-12 | 四川九洲电器集团有限责任公司 | Flight path updating method and flight path updating device |
CN106021675A (en) * | 2016-05-13 | 2016-10-12 | 国家海洋局第三海洋研究所 | Multisource automobile identifying system data-based data fusion method |
CN106094606A (en) * | 2016-05-19 | 2016-11-09 | 南通航运职业技术学院 | A kind of unmanned surface vehicle navigation and control remote-controlled operation platform |
CN106101590A (en) * | 2016-06-23 | 2016-11-09 | 上海无线电设备研究所 | The detection of radar video complex data and processing system and detection and processing method |
CN106446519A (en) * | 2016-08-31 | 2017-02-22 | 成都中星世通电子科技有限公司 | Ocean electronic data association method |
CN106816038A (en) * | 2017-03-17 | 2017-06-09 | 武汉理工大学 | A kind of inland waters abnormal behaviour ship automatic identification system and method |
CN107577230A (en) * | 2017-08-16 | 2018-01-12 | 武汉理工大学 | A kind of intelligent avoidance collision system towards unmanned boat |
CN107886773A (en) * | 2017-10-19 | 2018-04-06 | 天津大学 | Situation degree of urgency quantitative analysis method can be met residing for a kind of ship based on information content |
CN107908925A (en) * | 2017-11-17 | 2018-04-13 | 中国电子科技集团公司第十四研究所 | A kind of increment of rotation occupy-place formula moving-target label automatic avoiding method |
CN108470491A (en) * | 2017-02-23 | 2018-08-31 | 中国人民解放军63891部队 | Radar detection aircraft color demonstration method |
CN108538088A (en) * | 2018-02-11 | 2018-09-14 | 江苏金海星导航科技有限公司 | Ship collision prediction technique based on positioning and device |
CN108828550A (en) * | 2018-08-03 | 2018-11-16 | 国网福建省电力有限公司 | A kind of sea cable regional boundary ship target method for detecting position |
CN108897272A (en) * | 2018-06-29 | 2018-11-27 | 南京海联智能科技有限公司 | Bank end intelligent monitoring system |
CN108917767A (en) * | 2018-06-28 | 2018-11-30 | 中国船舶重工集团公司第七0七研究所 | A kind of navigation sport plotting calculation method based on electronic chart |
CN109166355A (en) * | 2018-07-20 | 2019-01-08 | 大连海事大学 | A kind of speed change avoidance system when river channel navigates by water |
CN109191916A (en) * | 2018-10-11 | 2019-01-11 | 苏州大学 | A kind of ship collision early warning system based on image |
CN109190170A (en) * | 2018-08-02 | 2019-01-11 | 哈尔滨工程大学 | A kind of Collision Risk Index modeling method based on cloud models theory |
CN109360450A (en) * | 2018-12-05 | 2019-02-19 | 福州大学 | A kind of vessel traffic service method and system of wisdom navigation mark |
CN109708638A (en) * | 2018-12-03 | 2019-05-03 | 江苏科技大学 | A kind of ship track point extracting method |
CN109856624A (en) * | 2019-01-03 | 2019-06-07 | 中国人民解放军空军研究院战略预警研究所 | A kind of Target state estimator method for single radar rectilinear path line |
CN109856625A (en) * | 2019-03-06 | 2019-06-07 | 国网福建省电力有限公司莆田供电公司 | A kind of vessel position recognition methods based on multisource data fusion |
CN109887339A (en) * | 2019-03-20 | 2019-06-14 | 集美大学 | A kind of ship collision danger and risk assessment method being associated with evacuation behavior |
CN109976342A (en) * | 2019-03-22 | 2019-07-05 | 智慧航海(青岛)科技有限公司 | A kind of intelligent ship multi-ship situation collision prevention method of News Search |
CN109996176A (en) * | 2019-05-20 | 2019-07-09 | 北京百度网讯科技有限公司 | Perception information method for amalgamation processing, device, terminal and storage medium |
CN110009937A (en) * | 2019-03-21 | 2019-07-12 | 武汉理工大学 | A kind of ship collision risk analysis method based on AIS data |
CN110009936A (en) * | 2019-03-15 | 2019-07-12 | 北京海兰信数据科技股份有限公司 | A kind of ship auxiliary collision prevention method for crowded waters |
CN110060281A (en) * | 2019-03-25 | 2019-07-26 | 同济大学 | A kind of ship and over-water floats trajectory track system |
CN110083155A (en) * | 2019-04-19 | 2019-08-02 | 集美大学 | Machine learning method for realizing ship anthropomorphic intelligent collision avoidance decision |
CN110164186A (en) * | 2019-06-18 | 2019-08-23 | 武汉理工大学 | Ship passes through confluence waters auxiliary collision avoidance system and method |
CN110164185A (en) * | 2019-06-05 | 2019-08-23 | 大连海事大学 | A kind of ship collision prevention system based on AIS |
CN110203325A (en) * | 2019-06-14 | 2019-09-06 | 上海外高桥造船有限公司 | The test method and system of the collision prevention function of ship autonomous navigation system |
CN110208803A (en) * | 2019-05-24 | 2019-09-06 | 中铁大桥科学研究院有限公司 | Shipping anti-collision radar monitors recognition methods at bridge |
CN110322731A (en) * | 2019-06-20 | 2019-10-11 | 武汉理工大学 | A kind of ship meeting navaid method for early warning |
CN110491171A (en) * | 2019-09-17 | 2019-11-22 | 南京莱斯网信技术研究院有限公司 | A kind of water transportation supervision early warning system and method based on machine learning techniques |
CN110749321A (en) * | 2019-10-22 | 2020-02-04 | 中国人民解放军海军潜艇学院 | Navigation drawing electronic auxiliary method, device and system |
CN110889221A (en) * | 2019-11-22 | 2020-03-17 | 武汉理工大学 | Method for establishing ship collision avoidance model based on non-Europe-preserving transformation |
CN110910337A (en) * | 2019-11-29 | 2020-03-24 | 珠海云航智能技术有限公司 | Ship track fusion method and device and terminal equipment |
CN110987068A (en) * | 2019-11-28 | 2020-04-10 | 中国人民解放军陆军炮兵防空兵学院郑州校区 | Data fusion method for multi-sensor integrated control system |
CN111028546A (en) * | 2019-11-20 | 2020-04-17 | 智慧航海(青岛)科技有限公司 | Multi-ship cooperative collision prevention system and method for intelligent ship based on shore-based radar |
CN111063218A (en) * | 2019-06-24 | 2020-04-24 | 武汉理工大学 | Ship collision avoidance decision method |
CN111176271A (en) * | 2019-11-21 | 2020-05-19 | 智慧航海(青岛)科技有限公司 | Intelligent ship collision avoidance aid decision-making system based on shore-based radar and implementation method thereof |
CN111221336A (en) * | 2020-01-19 | 2020-06-02 | 智慧航海(青岛)科技有限公司 | Ship-end auxiliary berthing-leaving system |
CN111243339A (en) * | 2020-01-14 | 2020-06-05 | 武汉理工大学 | AIS system and method special for ferry with collision avoidance early warning function |
CN111272171A (en) * | 2020-04-07 | 2020-06-12 | 上海船舶研究设计院(中国船舶工业集团公司第六0四研究院) | Ship track prediction method and device |
CN111309201A (en) * | 2020-01-19 | 2020-06-19 | 青岛海狮网络科技有限公司 | Multi-window display method for autonomous collision avoidance of autonomously driven ship |
CN111337027A (en) * | 2019-12-27 | 2020-06-26 | 北京海兰信数据科技股份有限公司 | Ship follow-up operation auxiliary driving method and system |
CN111915928A (en) * | 2020-06-28 | 2020-11-10 | 大连海事大学 | Ship collision accident rate prediction method |
CN111932944A (en) * | 2020-07-07 | 2020-11-13 | 智慧航海(青岛)智能系统工程有限公司 | Method for carrying out data processing at ship end based on regional ship data |
CN111951606A (en) * | 2020-07-29 | 2020-11-17 | 武汉理工大学 | Ship collision risk assessment and early warning method and system |
CN111968406A (en) * | 2020-08-18 | 2020-11-20 | 江苏航运职业技术学院 | Chaos theory-based fuzzy prediction method for short-term traffic flow of ship |
CN112362042A (en) * | 2020-10-30 | 2021-02-12 | 智慧航海(青岛)科技有限公司 | Track association judgment method based on intelligent ship multi-sensor equipment |
CN112364795A (en) * | 2020-11-18 | 2021-02-12 | 大连海事大学 | Method for automatically identifying signal lamp and sensing meeting situation of two ships |
CN113009470A (en) * | 2021-02-09 | 2021-06-22 | 北京理工大学 | Target situation characteristic data processing method, system, device and medium |
CN113010958A (en) * | 2019-12-20 | 2021-06-22 | 财团法人船舶暨海洋产业研发中心 | Simulation system of self-propelled ship and operation method thereof |
CN113380072A (en) * | 2021-05-21 | 2021-09-10 | 山东交通学院 | Ship safety protection method |
CN113470435A (en) * | 2021-07-09 | 2021-10-01 | 上海海事大学 | Method and terminal for generating intelligent ship test scene of natural anti-marine environment |
CN113744569A (en) * | 2021-11-03 | 2021-12-03 | 武汉理工大学 | Autonomous collision avoidance method, system, equipment and storage medium for ships in open water |
CN113744570A (en) * | 2021-11-03 | 2021-12-03 | 武汉理工大学 | Anti-collision early warning method and device for ships in water area of bridge area |
CN114464015A (en) * | 2022-02-08 | 2022-05-10 | 北京百度网讯科技有限公司 | Data processing method, data processing device, electronic equipment and storage medium |
CN114464014A (en) * | 2022-01-05 | 2022-05-10 | 集美大学 | Fuzzy logic based regional ship collision risk processing method, system and medium |
CN114495583A (en) * | 2021-12-24 | 2022-05-13 | 福建新继船舶服务有限公司 | Anti-collision method based on DQN-BP model |
CN114664118A (en) * | 2022-03-18 | 2022-06-24 | 陕西正整数科技有限公司 | Intelligent ship collision avoidance automatic test scene generation method and system |
CN114846530A (en) * | 2019-12-25 | 2022-08-02 | 下川部知洋 | Management server in ship navigation support system, ship navigation support method, and ship navigation support program |
CN115273556A (en) * | 2022-06-24 | 2022-11-01 | 大连海事大学 | Ship collision avoidance decision method and system based on interoperation technology |
CN115410420A (en) * | 2022-10-31 | 2022-11-29 | 河北东来工程技术服务有限公司 | Ship safe navigation management method and system |
CN115472041A (en) * | 2022-11-14 | 2022-12-13 | 福建飞通通讯科技股份有限公司 | Novel marine boats and ships meet early warning reminder system |
WO2023138053A1 (en) * | 2022-01-18 | 2023-07-27 | 舟山市质量技术监督检测研究院 | Track fusion method and apparatus for unmanned surface vehicle |
CN117292583A (en) * | 2023-10-11 | 2023-12-26 | 绒智海试科技(河北)有限公司 | Target object situation display system based on comprehensive situation display and plotting |
US11934652B2 (en) | 2020-10-14 | 2024-03-19 | Samsung Electronics Co., Ltd. | Display apparatus and control method thereof |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103714718A (en) * | 2013-12-31 | 2014-04-09 | 武汉理工大学 | Inland river bridge area ship safe navigation precontrol system |
US20140111368A1 (en) * | 2012-10-22 | 2014-04-24 | Electronics And Telecommunications Research Institute | Method and system for managing traffic considering gps jamming |
CN104391281A (en) * | 2014-11-21 | 2015-03-04 | 武汉大学 | Method for improving sky-wave radar sea surface ship target tracking and positioning precision |
-
2015
- 2015-11-06 CN CN201510755138.7A patent/CN105390029B/en not_active Expired - Fee Related
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140111368A1 (en) * | 2012-10-22 | 2014-04-24 | Electronics And Telecommunications Research Institute | Method and system for managing traffic considering gps jamming |
CN103714718A (en) * | 2013-12-31 | 2014-04-09 | 武汉理工大学 | Inland river bridge area ship safe navigation precontrol system |
CN104391281A (en) * | 2014-11-21 | 2015-03-04 | 武汉大学 | Method for improving sky-wave radar sea surface ship target tracking and positioning precision |
Non-Patent Citations (1)
Title |
---|
吴红双: "《基于AIS/雷达融合信息的船舶避碰终端设计与实现》", 《CNKI中国优秀硕士论文全文数据库》 * |
Cited By (97)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105589464A (en) * | 2016-03-28 | 2016-05-18 | 哈尔滨工程大学 | UUV dynamic obstacle avoidance method based on speed obstruction method |
CN105589464B (en) * | 2016-03-28 | 2019-02-26 | 哈尔滨工程大学 | A kind of UUV dynamic obstacle avoidance method based on Speed Obstacles method |
CN106021675A (en) * | 2016-05-13 | 2016-10-12 | 国家海洋局第三海洋研究所 | Multisource automobile identifying system data-based data fusion method |
CN106094606A (en) * | 2016-05-19 | 2016-11-09 | 南通航运职业技术学院 | A kind of unmanned surface vehicle navigation and control remote-controlled operation platform |
CN106101590B (en) * | 2016-06-23 | 2019-07-19 | 上海无线电设备研究所 | The detection of radar video complex data and processing system and detection and processing method |
CN106101590A (en) * | 2016-06-23 | 2016-11-09 | 上海无线电设备研究所 | The detection of radar video complex data and processing system and detection and processing method |
CN106017475A (en) * | 2016-07-04 | 2016-10-12 | 四川九洲电器集团有限责任公司 | Flight path updating method and flight path updating device |
CN106017475B (en) * | 2016-07-04 | 2019-03-08 | 四川九洲防控科技有限责任公司 | A kind of track update method and device |
CN106446519A (en) * | 2016-08-31 | 2017-02-22 | 成都中星世通电子科技有限公司 | Ocean electronic data association method |
CN106446519B (en) * | 2016-08-31 | 2019-04-05 | 成都中星世通电子科技有限公司 | A kind of Marine Electronics data correlation method |
CN108470491A (en) * | 2017-02-23 | 2018-08-31 | 中国人民解放军63891部队 | Radar detection aircraft color demonstration method |
CN106816038A (en) * | 2017-03-17 | 2017-06-09 | 武汉理工大学 | A kind of inland waters abnormal behaviour ship automatic identification system and method |
CN106816038B (en) * | 2017-03-17 | 2019-06-11 | 武汉理工大学 | A kind of inland waters abnormal behaviour ship automatic identification system and method |
CN107577230A (en) * | 2017-08-16 | 2018-01-12 | 武汉理工大学 | A kind of intelligent avoidance collision system towards unmanned boat |
CN107577230B (en) * | 2017-08-16 | 2020-01-14 | 武汉理工大学 | Intelligent collision avoidance system for unmanned ship |
CN107886773B (en) * | 2017-10-19 | 2020-12-11 | 天津大学 | Information quantity-based quantitative analysis method for urgency of meeting situation of ship |
CN107886773A (en) * | 2017-10-19 | 2018-04-06 | 天津大学 | Situation degree of urgency quantitative analysis method can be met residing for a kind of ship based on information content |
CN107908925A (en) * | 2017-11-17 | 2018-04-13 | 中国电子科技集团公司第十四研究所 | A kind of increment of rotation occupy-place formula moving-target label automatic avoiding method |
CN108538088A (en) * | 2018-02-11 | 2018-09-14 | 江苏金海星导航科技有限公司 | Ship collision prediction technique based on positioning and device |
CN108917767B (en) * | 2018-06-28 | 2021-01-26 | 中国船舶重工集团公司第七0七研究所 | Electronic chart-based navigation motion plotting calculation method |
CN108917767A (en) * | 2018-06-28 | 2018-11-30 | 中国船舶重工集团公司第七0七研究所 | A kind of navigation sport plotting calculation method based on electronic chart |
CN108897272A (en) * | 2018-06-29 | 2018-11-27 | 南京海联智能科技有限公司 | Bank end intelligent monitoring system |
CN109166355A (en) * | 2018-07-20 | 2019-01-08 | 大连海事大学 | A kind of speed change avoidance system when river channel navigates by water |
CN109166355B (en) * | 2018-07-20 | 2021-08-03 | 大连海事大学 | Variable speed avoiding system during navigation of ship channel |
CN109190170A (en) * | 2018-08-02 | 2019-01-11 | 哈尔滨工程大学 | A kind of Collision Risk Index modeling method based on cloud models theory |
CN108828550A (en) * | 2018-08-03 | 2018-11-16 | 国网福建省电力有限公司 | A kind of sea cable regional boundary ship target method for detecting position |
CN109191916A (en) * | 2018-10-11 | 2019-01-11 | 苏州大学 | A kind of ship collision early warning system based on image |
CN109708638A (en) * | 2018-12-03 | 2019-05-03 | 江苏科技大学 | A kind of ship track point extracting method |
CN109360450A (en) * | 2018-12-05 | 2019-02-19 | 福州大学 | A kind of vessel traffic service method and system of wisdom navigation mark |
CN109856624A (en) * | 2019-01-03 | 2019-06-07 | 中国人民解放军空军研究院战略预警研究所 | A kind of Target state estimator method for single radar rectilinear path line |
CN109856624B (en) * | 2019-01-03 | 2021-03-16 | 中国人民解放军空军研究院战略预警研究所 | Target state estimation method for single-radar linear flight path line |
CN109856625A (en) * | 2019-03-06 | 2019-06-07 | 国网福建省电力有限公司莆田供电公司 | A kind of vessel position recognition methods based on multisource data fusion |
CN110009936A (en) * | 2019-03-15 | 2019-07-12 | 北京海兰信数据科技股份有限公司 | A kind of ship auxiliary collision prevention method for crowded waters |
CN109887339A (en) * | 2019-03-20 | 2019-06-14 | 集美大学 | A kind of ship collision danger and risk assessment method being associated with evacuation behavior |
CN110009937A (en) * | 2019-03-21 | 2019-07-12 | 武汉理工大学 | A kind of ship collision risk analysis method based on AIS data |
CN109976342A (en) * | 2019-03-22 | 2019-07-05 | 智慧航海(青岛)科技有限公司 | A kind of intelligent ship multi-ship situation collision prevention method of News Search |
CN110060281A (en) * | 2019-03-25 | 2019-07-26 | 同济大学 | A kind of ship and over-water floats trajectory track system |
CN110060281B (en) * | 2019-03-25 | 2023-02-28 | 同济大学 | Ship and water floater track tracking system |
CN110083155A (en) * | 2019-04-19 | 2019-08-02 | 集美大学 | Machine learning method for realizing ship anthropomorphic intelligent collision avoidance decision |
CN109996176A (en) * | 2019-05-20 | 2019-07-09 | 北京百度网讯科技有限公司 | Perception information method for amalgamation processing, device, terminal and storage medium |
CN110208803A (en) * | 2019-05-24 | 2019-09-06 | 中铁大桥科学研究院有限公司 | Shipping anti-collision radar monitors recognition methods at bridge |
CN110164185A (en) * | 2019-06-05 | 2019-08-23 | 大连海事大学 | A kind of ship collision prevention system based on AIS |
CN110203325A (en) * | 2019-06-14 | 2019-09-06 | 上海外高桥造船有限公司 | The test method and system of the collision prevention function of ship autonomous navigation system |
CN110164186A (en) * | 2019-06-18 | 2019-08-23 | 武汉理工大学 | Ship passes through confluence waters auxiliary collision avoidance system and method |
CN110322731A (en) * | 2019-06-20 | 2019-10-11 | 武汉理工大学 | A kind of ship meeting navaid method for early warning |
CN110322731B (en) * | 2019-06-20 | 2021-08-10 | 武汉理工大学 | Ship meeting navigation aid early warning method |
CN111063218A (en) * | 2019-06-24 | 2020-04-24 | 武汉理工大学 | Ship collision avoidance decision method |
CN110491171A (en) * | 2019-09-17 | 2019-11-22 | 南京莱斯网信技术研究院有限公司 | A kind of water transportation supervision early warning system and method based on machine learning techniques |
CN110749321A (en) * | 2019-10-22 | 2020-02-04 | 中国人民解放军海军潜艇学院 | Navigation drawing electronic auxiliary method, device and system |
CN111028546A (en) * | 2019-11-20 | 2020-04-17 | 智慧航海(青岛)科技有限公司 | Multi-ship cooperative collision prevention system and method for intelligent ship based on shore-based radar |
CN111176271B (en) * | 2019-11-21 | 2023-05-02 | 智慧航海(青岛)科技有限公司 | Intelligent ship collision avoidance auxiliary decision-making system based on shore radar and implementation method thereof |
CN111176271A (en) * | 2019-11-21 | 2020-05-19 | 智慧航海(青岛)科技有限公司 | Intelligent ship collision avoidance aid decision-making system based on shore-based radar and implementation method thereof |
CN110889221B (en) * | 2019-11-22 | 2022-06-17 | 武汉理工大学 | Method for establishing ship collision avoidance model based on non-Europe-preserving transformation |
CN110889221A (en) * | 2019-11-22 | 2020-03-17 | 武汉理工大学 | Method for establishing ship collision avoidance model based on non-Europe-preserving transformation |
CN110987068B (en) * | 2019-11-28 | 2021-11-30 | 中国人民解放军陆军炮兵防空兵学院郑州校区 | Data fusion method for multi-sensor integrated control system |
CN110987068A (en) * | 2019-11-28 | 2020-04-10 | 中国人民解放军陆军炮兵防空兵学院郑州校区 | Data fusion method for multi-sensor integrated control system |
CN110910337A (en) * | 2019-11-29 | 2020-03-24 | 珠海云航智能技术有限公司 | Ship track fusion method and device and terminal equipment |
CN113010958A (en) * | 2019-12-20 | 2021-06-22 | 财团法人船舶暨海洋产业研发中心 | Simulation system of self-propelled ship and operation method thereof |
CN114846530A (en) * | 2019-12-25 | 2022-08-02 | 下川部知洋 | Management server in ship navigation support system, ship navigation support method, and ship navigation support program |
CN111337027A (en) * | 2019-12-27 | 2020-06-26 | 北京海兰信数据科技股份有限公司 | Ship follow-up operation auxiliary driving method and system |
CN111243339A (en) * | 2020-01-14 | 2020-06-05 | 武汉理工大学 | AIS system and method special for ferry with collision avoidance early warning function |
CN111221336B (en) * | 2020-01-19 | 2023-06-30 | 智慧航海(青岛)科技有限公司 | Ship end auxiliary leaning and off-berthing system |
CN111221336A (en) * | 2020-01-19 | 2020-06-02 | 智慧航海(青岛)科技有限公司 | Ship-end auxiliary berthing-leaving system |
CN111309201A (en) * | 2020-01-19 | 2020-06-19 | 青岛海狮网络科技有限公司 | Multi-window display method for autonomous collision avoidance of autonomously driven ship |
CN111272171B (en) * | 2020-04-07 | 2023-05-30 | 上海船舶研究设计院(中国船舶工业集团公司第六0四研究院) | Ship track prediction method and device |
CN111272171A (en) * | 2020-04-07 | 2020-06-12 | 上海船舶研究设计院(中国船舶工业集团公司第六0四研究院) | Ship track prediction method and device |
CN111915928B (en) * | 2020-06-28 | 2022-04-26 | 大连海事大学 | Ship collision accident rate prediction method |
CN111915928A (en) * | 2020-06-28 | 2020-11-10 | 大连海事大学 | Ship collision accident rate prediction method |
CN111932944A (en) * | 2020-07-07 | 2020-11-13 | 智慧航海(青岛)智能系统工程有限公司 | Method for carrying out data processing at ship end based on regional ship data |
CN111951606A (en) * | 2020-07-29 | 2020-11-17 | 武汉理工大学 | Ship collision risk assessment and early warning method and system |
CN111951606B (en) * | 2020-07-29 | 2021-07-30 | 武汉理工大学 | Ship collision risk assessment and early warning method and system |
CN111968406B (en) * | 2020-08-18 | 2021-06-25 | 江苏航运职业技术学院 | Chaos theory-based fuzzy prediction method for short-term traffic flow of ship |
CN111968406A (en) * | 2020-08-18 | 2020-11-20 | 江苏航运职业技术学院 | Chaos theory-based fuzzy prediction method for short-term traffic flow of ship |
US11934652B2 (en) | 2020-10-14 | 2024-03-19 | Samsung Electronics Co., Ltd. | Display apparatus and control method thereof |
CN112362042A (en) * | 2020-10-30 | 2021-02-12 | 智慧航海(青岛)科技有限公司 | Track association judgment method based on intelligent ship multi-sensor equipment |
CN112362042B (en) * | 2020-10-30 | 2023-03-10 | 智慧航海(青岛)科技有限公司 | Track correlation judgment method based on intelligent ship multi-sensing equipment |
CN112364795A (en) * | 2020-11-18 | 2021-02-12 | 大连海事大学 | Method for automatically identifying signal lamp and sensing meeting situation of two ships |
CN112364795B (en) * | 2020-11-18 | 2024-01-30 | 大连海事大学 | Automatic identification method for number lamps and situation awareness method for two ships meeting |
CN113009470A (en) * | 2021-02-09 | 2021-06-22 | 北京理工大学 | Target situation characteristic data processing method, system, device and medium |
CN113009470B (en) * | 2021-02-09 | 2023-04-21 | 北京理工大学 | Processing method, system, device and medium for target situation characteristic data |
CN113380072A (en) * | 2021-05-21 | 2021-09-10 | 山东交通学院 | Ship safety protection method |
CN113380072B (en) * | 2021-05-21 | 2022-04-26 | 山东交通学院 | Ship safety protection method |
CN113470435A (en) * | 2021-07-09 | 2021-10-01 | 上海海事大学 | Method and terminal for generating intelligent ship test scene of natural anti-marine environment |
CN113744570B (en) * | 2021-11-03 | 2022-03-25 | 武汉理工大学 | Anti-collision early warning method and device for ships in water area of bridge area |
CN113744570A (en) * | 2021-11-03 | 2021-12-03 | 武汉理工大学 | Anti-collision early warning method and device for ships in water area of bridge area |
CN113744569A (en) * | 2021-11-03 | 2021-12-03 | 武汉理工大学 | Autonomous collision avoidance method, system, equipment and storage medium for ships in open water |
CN114495583A (en) * | 2021-12-24 | 2022-05-13 | 福建新继船舶服务有限公司 | Anti-collision method based on DQN-BP model |
CN114464014A (en) * | 2022-01-05 | 2022-05-10 | 集美大学 | Fuzzy logic based regional ship collision risk processing method, system and medium |
WO2023138053A1 (en) * | 2022-01-18 | 2023-07-27 | 舟山市质量技术监督检测研究院 | Track fusion method and apparatus for unmanned surface vehicle |
CN114464015A (en) * | 2022-02-08 | 2022-05-10 | 北京百度网讯科技有限公司 | Data processing method, data processing device, electronic equipment and storage medium |
CN114464015B (en) * | 2022-02-08 | 2023-05-02 | 北京百度网讯科技有限公司 | Data processing method, device, electronic equipment and storage medium |
CN114664118B (en) * | 2022-03-18 | 2023-04-07 | 陕西正整数科技有限公司 | Intelligent ship collision avoidance automatic test scene generation method and system |
CN114664118A (en) * | 2022-03-18 | 2022-06-24 | 陕西正整数科技有限公司 | Intelligent ship collision avoidance automatic test scene generation method and system |
CN115273556A (en) * | 2022-06-24 | 2022-11-01 | 大连海事大学 | Ship collision avoidance decision method and system based on interoperation technology |
CN115410420A (en) * | 2022-10-31 | 2022-11-29 | 河北东来工程技术服务有限公司 | Ship safe navigation management method and system |
CN115472041A (en) * | 2022-11-14 | 2022-12-13 | 福建飞通通讯科技股份有限公司 | Novel marine boats and ships meet early warning reminder system |
CN117292583A (en) * | 2023-10-11 | 2023-12-26 | 绒智海试科技(河北)有限公司 | Target object situation display system based on comprehensive situation display and plotting |
Also Published As
Publication number | Publication date |
---|---|
CN105390029B (en) | 2019-04-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105390029A (en) | Ship collision avoidance assisted decision-making method and system based on track fusion and track prediction | |
Du et al. | Improving stand-on ship's situational awareness by estimating the intention of the give-way ship | |
CN109460218B (en) | Ship-end integrated navigation system architecture | |
CN112966332B (en) | Conflict detection method based on multi-ship motion uncertainty, memory and processor | |
CN104732806A (en) | Automatic ship-bridge collision risk recognizing and pre-warning system | |
Shi et al. | Fuzzy logic-based modeling method for regional multi-ship collision risk assessment considering impacts of ship crossing angle and navigational environment | |
CN113536544B (en) | Ship probability conflict detection method based on minimum safe distance model | |
Ma et al. | A data-driven approach for collision risk early warning in vessel encounter situations using attention-BiLSTM | |
Qiao et al. | A collision risk identification method for autonomous ships based on field theory | |
CN111025295A (en) | Multi-ship cooperative sensing data fusion system and method based on shore-based radar | |
Zhao et al. | Ship surveillance by integration of space-borne SAR and AIS–further research | |
Zheng et al. | A Decision‐Making Method for Ship Collision Avoidance Based on Improved Cultural Particle Swarm | |
Silveira et al. | Assessment of ship collision estimation methods using AIS data | |
Wu et al. | A new multi-sensor fusion approach for integrated ship motion perception in inland waterways | |
CN111898835A (en) | Intelligent traffic management method, device, computer and readable storage medium | |
CN203094401U (en) | Shipborne automatic identification system (AIS) automatic intelligent collision prevention system adopting sonar detection | |
Wang et al. | A real-time ship collision risk perception model derived from domain-based approach parameters | |
CN115723919A (en) | Auxiliary navigation method and device for ship yaw | |
Steidel et al. | MTCAS–an assistance system for collision avoidance at sea | |
Vestre et al. | AIS-based near-collision database generation and analysis of real collision avoidance manoeuvres | |
Firl et al. | MARV-X: Applying maneuver assessment for reliable verification of car-to-X mobility data | |
Liu et al. | A conflict cluster-based method for collision avoidance decision-making in multi-ship encounter situations | |
Chen et al. | Risk assessment methods for ship collision in estuarine waters using AIS and historical accident data | |
Liu et al. | Coordinated multi-stage and multi-objective optimization approach for ship collision avoidance decision-making | |
Lamm et al. | Detecting maneuvers in maritime observation data with CUSUM |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190426 |